ABSTRACT
Regulating the structural and interfacial properties of transition metal phosphides (TMPs) by coupling carbon-based materials with large surface areas to enhance hydrogen evolution reaction (HER) performance presents significant progress for water splitting technology. Herein, we constructed a composite substrate of a three-dimensional porous graphene oxide matrix (3D-GO) embedded in nickel foam (NF) to grow a Co2P electrocatalyst. Well-defined gladiolus-like Co2P nanowire arrays tightly anchored on the substrate show enhanced electrochemical characteristics for the hydrogen evolution reaction (HER) based on the promoting roles of 3D porous reduced GO (3D-rGO) derived from 3D-GO, which promotes the dispersion of active components, improves the rate of electron transfer, and facilitates the transport of water molecules. As a result, the obtained Co2P@3D-rGO/NF electrode exhibits superior HER activity in 1.0 M KOH media, achieving overpotentials of 36.5 and 264.7 mV at current densities of 10 and 100 mA cm-2, respectively. The electrode also has a low Tafel slope of 55.5 mV dec-1, a large electrochemical surface area, and small charge-transfer resistance, further revealing its mechanism of high intrinsic activity. Moreover, the electrode exhibits excellent HER stability and durability without surface morphology and chemical state changes.
ABSTRACT
With the wide application of convolutional neural networks (CNNs), a variety of ship detection methods based on CNNs in synthetic aperture radar (SAR) images were proposed, but there are still two main challenges: (1) Ship detection requires high real-time performance, and a certain detection speed should be ensured while improving accuracy; (2) The diversity of ships in SAR images requires more powerful multi-scale detectors. To address these issues, a SAR ship detector called Duplicate Bilateral YOLO (DB-YOLO) is proposed in this paper, which is composed of a Feature Extraction Network (FEN), Duplicate Bilateral Feature Pyramid Network (DB-FPN) and Detection Network (DN). Firstly, a single-stage network is used to meet the need of real-time detection, and the cross stage partial (CSP) block is used to reduce the redundant parameters. Secondly, DB-FPN is designed to enhance the fusion of semantic and spatial information. In view of the ships in SAR image are mainly distributed with small-scale targets, the distribution of parameters and computation values between FEN and DB-FPN in different feature layers is redistributed to solve the multi-scale detection. Finally, the bounding boxes and confidence scores are given through the detection head of YOLO. In order to evaluate the effectiveness and robustness of DB-YOLO, comparative experiments with the other six state-of-the-art methods (Faster R-CNN, Cascade R-CNN, Libra R-CNN, FCOS, CenterNet and YOLOv5s) on two SAR ship datasets, i.e., SSDD and HRSID, are performed. The experimental results show that the AP50 of DB-YOLO reaches 97.8% on SSDD and 94.4% on HRSID, respectively. DB-YOLO meets the requirement of real-time detection (48.1 FPS) and is superior to other methods in the experiments.
Subject(s)
Radar , Ships , Neural Networks, Computer , Records , SemanticsABSTRACT
BACKGROUND: King Vision and McGrath MAC video laryngoscopes (VLs) are increasingly used. The purpose of this study was to evaluate the performance of nasotracheal intubation in patients with predicted difficult intubations using non-channeled King Vision VL, McGrath MAC VL or Macintosh laryngoscope by experienced intubators. METHODS: Ninety nine ASA I or II adult patients, scheduled for oral maxillofacial surgeries with El-Ganzouri risk index 1-7 were enrolled. Patients were randomly allocated to intubate with one of three laryngoscopes (non-channeled King Vision, McGrath MAC and Macintosh). The intubators were experienced with more than 100 successful nasotracheal intubations using each device. The primary outcome was intubation time. The secondary outcomes included first success rate, time required for viewing the glottis, Cormack-Lehane grade of glottis view, the number of assist maneuvers, hemodynamic responses, the subjective evaluating of sensations of performances and associated complications. RESULTS: The intubation time of King Vision and McGrath group was comparable (37.6 ± 7.3 s vs. 35.4 ± 8.8 s) and both were shorter than Macintosh group (46.8 ± 10.4 s, p < 0.001). Both King Vision and McGrath groups had a 100% first attempt success rate, significantly higher than Macintosh group (85%, p < 0.05). The laryngoscopy time was comparable between King Vision and McGrath group (16.7 ± 5.5 s vs. 15.6 ± 6.3 s) and was shorter than Macintosh group (22.8 ± 7.2 s, p < 0.05) also. Compared with Macintosh laryngoscope, Glottis view was obviously improved when exposed with either non-channeled King Vision or McGrath MAC VL (p < 0.001), and assist maneuvers required were reduced (p < 0.001). The maximum fluctuations of MAP were significantly attenuated in VL groups (47.7 ± 12.5 mmHg and 45.1 ± 10.3 mmHg vs. 54.9 ± 10.2 mmHg, p < 0.05 and p < 0.01). Most device insertions were graded as excellent in McGrath group, followed by Macintosh and King Vision group (p = 0.0014). The tube advancements were easier in VLs compared with the Macintosh laryngoscope (p < 0.001). Sore throat was found more frequent in Macintosh group compared with King Vision group (p < 0.05). CONCLUSIONS: Non-channeled King Vision and McGrath MAC VLs were comparable and both devices facilitated nasotracheal intubation in managing predicted difficult intubations compared with Macintosh laryngoscope. TRIAL REGISTRATION: ClinicalTrials registration number NCT03126344 . Registered on April 24, 2017.
